Social Network Analysis: A Practical Introduction for Beginners Jonathan Rubright, MS Steve Fifield, PhD Delaware Education Research and Development Center EERS 19 April 2010

SNA: What is it? "the mapping and measuring of relationships and flows between people, groups, organizations, computers or other information/knowledge processing entities." (Valdis Krebs, 2002) Nodes People, Organizations . . . Connected by Ties Relationship existence and strength Form analyzable Patterns Social network analysis helps reveal real network outside organizational charts, and can identify boundaries of flow and connection.

Sociogram example

Before and After What changed? What remains similar? 2006 2008

2006 2008 Yellow=Clinician Green=Clinician/Scientist Blue=Scientist White=NR

Common Issues & Applications Formal vs. informal organizational structures & processes Key individuals & subgroups Information flow & supportiveness Changing practices & changing relationships

Data Collection Considerations Unbounded network data (name-generator) Social networks reported by individuals Bounded network data (roster approach) Network boundaries with complete list of members

Unbounded Network data Which people in the neighborhood would you trust to look after your child? At work, in neighborhood – how define?

Bounded network data Which of these people in the neighborhood would you trust to look after your child? Name Trust to look after? Susan Yes / No Jill Tommy Billy Bounded networks not able to draw from outside members, yet often produce more connected networks.

Data Setup Most familiar datasets have a set of cases with variables on each case… Name Sex Age Role Jack M 22 Admin Jill F 35 Director Andre 68 Sandra 42 Financial

Data Setup 2 Most SNA datasets are matrices with nodes in both rows and columns Cells represent relationships between nodes Jack Jill Andre Sandra . 1

Methodological Considerations Missing data can seriously distort network Limiting number of network choices truncates the network Informant fatigue Limitations of self report Inconsistent definition of relations Dynamic nature of networks

Data Collection Example Complete network data Have you met this person before this session at EERS? Data organization, management, analysis

Connectedness Identifying characteristics of individual actors based on their relationships with others in the network Examples: indegree, outdegree,betweenness Identifying characteristics of subgroups in the network Identifying characteristics of the network as a whole Density

Questions and Comments? Questions you might like to answer using social network analysis?

Thank you! Jonathan Rubright, rubright@udel.edu Steve Fifield, fifield@udel.edu

Bibliography of Resources Books Websites

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2006 Yellow=Clinician Green=Clinician/Scientist Blue=Scientist White=NR 20

2008 Yellow=Clinician Green=Clinician/Scientist Blue=Scientist White=NR

SPSS Code Example *Extract data from master data file for anonymous collaborative network analysis. *Research colloborator before? *First I will load the main Excel dataset into SPSS. GET DATA /TYPE=XLS /FILE='C:\Documents and Settings\rubright\Desktop\data_clean_ impute.xls' /SHEET=name 'Sheet1' /CELLRANGE=full /READNAMES=on /ASSUMEDSTRWIDTH=32767. DATASET NAME DataSet1 WINDOW=FRONT. *I'll rename the variables names for easier use in UCINet. RENAME VARIABLE (John_before=John). RENAME VARIABLE (Steve_before=Steve). *Finally, I will save the updated dataset as an Excel file named before_anon.xls, only variables usable in UCINet. SAVE TRANSLATE OUTFILE='C:\Documents and Settings\rubright\Desktop\before_nr_anon.xls' /VERSION=8 /MAP /REPLACE /FIELDNAMES /CELLS=VALUES /KEEP= ID John Steve.